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README.md
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README.md
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<div align="center">
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<h1>Retrieval-based-Voice-Conversion-WebUI</h1>
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An easy-to-use Voice Conversion framework based on VITS.<br><br>
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一个基于VITS的简单易用的语音转换（变声器）框架<br><br>
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[](https://github.com/RVC-Project/Retrieval-based-Voice-Conversion-WebUI)
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<img src="https://counter.seku.su/cmoe?name=rvc&theme=r34" /><br>
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[](https://colab.research.google.com/github/RVC-Project/Retrieval-based-Voice-Conversion-WebUI/blob/main/Retrieval_based_Voice_Conversion_WebUI.ipynb)
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[](https://github.com/RVC-Project/Retrieval-based-Voice-Conversion-WebUI/blob/main/LICENSE)
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[](https://github.com/RVC-Project/Retrieval-based-Voice-Conversion-WebUI/blob/main/LICENSE)
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[](https://huggingface.co/lj1995/VoiceConversionWebUI/tree/main/)
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[](https://discord.gg/HcsmBBGyVk)
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[**更新日志**](https://github.com/RVC-Project/Retrieval-based-Voice-Conversion-WebUI/blob/main/docs/Changelog_CN.md) | [**常见问题解答**](https://github.com/RVC-Project/Retrieval-based-Voice-Conversion-WebUI/wiki/%E5%B8%B8%E8%A7%81%E9%97%AE%E9%A2%98%E8%A7%A3%E7%AD%94) | [**AutoDL·5毛钱训练AI歌手**](https://github.com/RVC-Project/Retrieval-based-Voice-Conversion-WebUI/wiki/Autodl%E8%AE%AD%E7%BB%83RVC%C2%B7AI%E6%AD%8C%E6%89%8B%E6%95%99%E7%A8%8B) | [**对照实验记录**](https://github.com/RVC-Project/Retrieval-based-Voice-Conversion-WebUI/wiki/Autodl%E8%AE%AD%E7%BB%83RVC%C2%B7AI%E6%AD%8C%E6%89%8B%E6%95%99%E7%A8%8B](https://github.com/RVC-Project/Retrieval-based-Voice-Conversion-WebUI/wiki/%E5%AF%B9%E7%85%A7%E5%AE%9E%E9%AA%8C%C2%B7%E5%AE%9E%E9%AA%8C%E8%AE%B0%E5%BD%95)) | [**在线演示**](https://huggingface.co/spaces/Ricecake123/RVC-demo)
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</div>
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------
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[**Changelog**](https://github.com/RVC-Project/Retrieval-based-Voice-Conversion-WebUI/blob/main/docs/Changelog_EN.md) | [**FAQ (Frequently Asked Questions)**](https://github.com/RVC-Project/Retrieval-based-Voice-Conversion-WebUI/wiki/FAQ-(Frequently-Asked-Questions))
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[**English**](../en/README.en.md) | [**中文简体**](../../README.md) | [**日本語**](../jp/README.ja.md) | [**한국어**](../kr/README.ko.md) ([**韓國語**](../kr/README.ko.han.md)) | [**Türkçe**](../tr/README.tr.md)
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[**English**](./docs/en/README.en.md) | [**中文简体**](./README.md) | [**日本語**](./docs/jp/README.ja.md) | [**한국어**](./docs/kr/README.ko.md) ([**韓國語**](./docs/kr/README.ko.han.md)) | [**Français**](./docs/fr/README.fr.md)| [**Türkçe**](./docs/tr/README.tr.md)
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点此查看我们的[演示视频](https://www.bilibili.com/video/BV1pm4y1z7Gm/) !
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Check our [Demo Video](https://www.bilibili.com/video/BV1pm4y1z7Gm/) here!
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> 使用了RVC的实时语音转换: [w-okada/voice-changer](https://github.com/w-okada/voice-changer)
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Realtime Voice Conversion Software using RVC : [w-okada/voice-changer](https://github.com/w-okada/voice-changer)
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> 底模使用接近50小时的开源高质量VCTK训练集训练，无版权方面的顾虑，请大家放心使用
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> 请期待RVCv3的底模，参数更大，数据更大，效果更好，基本持平的推理速度，需要训练数据量更少。
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> The dataset for the pre-training model uses nearly 50 hours of high quality VCTK open source dataset.
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## 简介
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本仓库具有以下特点
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+ 使用top1检索替换输入源特征为训练集特征来杜绝音色泄漏
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+ 即便在相对较差的显卡上也能快速训练
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+ 使用少量数据进行训练也能得到较好结果(推荐至少收集10分钟低底噪语音数据)
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+ 可以通过模型融合来改变音色(借助ckpt处理选项卡中的ckpt-merge)
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+ 简单易用的网页界面
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+ 可调用UVR5模型来快速分离人声和伴奏
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+ 使用最先进的[人声音高提取算法InterSpeech2023-RMVPE](#参考项目)根绝哑音问题。效果最好（显著地）但比crepe_full更快、资源占用更小
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+ A卡I卡加速支持
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> High quality licensed song datasets will be added to training-set one after another for your use, without worrying about copyright infringement.
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## 环境配置
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以下指令需在 Python 版本大于3.8的环境中执行。
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> Please look forward to the pretrained base model of RVCv3, which has larger parameters, more training data, better results, unchanged inference speed, and requires less training data for training.
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## Summary
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This repository has the following features:
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+ Reduce tone leakage by replacing the source feature to training-set feature using top1 retrieval;
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+ Easy and fast training, even on relatively poor graphics cards;
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+ Training with a small amount of data also obtains relatively good results (>=10min low noise speech recommended);
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+ Supporting model fusion to change timbres (using ckpt processing tab->ckpt merge);
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+ Easy-to-use Webui interface;
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+ Use the UVR5 model to quickly separate vocals and instruments.
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+ Use the most powerful High-pitch Voice Extraction Algorithm [InterSpeech2023-RMVPE](#Credits) to prevent the muted sound problem. Provides the best results (significantly) and is faster, with even lower resource consumption than Crepe_full.
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+ AMD/Intel graphics cards acceleration supported.
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+ Intel ARC graphics cards acceleration with IPEX supported.
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## Preparing the environment
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The following commands need to be executed in the environment of Python version 3.8 or higher.
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(Windows/Linux)
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First install the main dependencies through pip:
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(Windows/Linux)
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首先通过 pip 安装主要依赖:
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```bash
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# Install PyTorch-related core dependencies, skip if installed
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# Reference: https://pytorch.org/get-started/locally/
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# 安装Pytorch及其核心依赖，若已安装则跳过
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# 参考自: https://pytorch.org/get-started/locally/
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pip install torch torchvision torchaudio
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#For Windows + Nvidia Ampere Architecture(RTX30xx), you need to specify the cuda version corresponding to pytorch according to the experience of https://github.com/RVC-Project/Retrieval-based-Voice-Conversion-WebUI/issues/21
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#如果是win系统+Nvidia Ampere架构(RTX30xx)，根据 #21 的经验，需要指定pytorch对应的cuda版本
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#pip install torch torchvision torchaudio --index-url https://download.pytorch.org/whl/cu117
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#For Linux + AMD Cards, you need to use the following pytorch versions:
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#pip install torch torchvision torchaudio --index-url https://download.pytorch.org/whl/rocm5.4.2
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```
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Then can use poetry to install the other dependencies:
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可以使用 poetry 来安装依赖：
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```bash
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# Install the Poetry dependency management tool, skip if installed
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# Reference: https://python-poetry.org/docs/#installation
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# 安装 Poetry 依赖管理工具, 若已安装则跳过
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# 参考自: https://python-poetry.org/docs/#installation
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curl -sSL https://install.python-poetry.org | python3 -
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# Install the project dependencies
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# 通过poetry安装依赖
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poetry install
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```
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You can also use pip to install them:
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你也可以通过 pip 来安装依赖：
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```bash
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N卡：
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for Nvidia graphics cards
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pip install -r requirements.txt
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pip install -r requirements.txt
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for AMD/Intel graphics cards on Windows (DirectML)：
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pip install -r requirements-dml.txt
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A卡/I卡：
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pip install -r requirements-dml.txt
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for Intel ARC graphics cards on Linux / WSL using Python 3.10:
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pip install -r requirements-ipex.txt
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for AMD graphics cards on Linux (ROCm):
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pip install -r requirements-amd.txt
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```
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------
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Mac users can install dependencies via `run.sh`:
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Mac 用户可以通过 `run.sh` 来安装依赖：
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```bash
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sh ./run.sh
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```
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## Preparation of other Pre-models
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RVC requires other pre-models to infer and train.
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## 其他预模型准备
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RVC需要其他一些预模型来推理和训练。
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You need to download them from our [Huggingface space](https://huggingface.co/lj1995/VoiceConversionWebUI/tree/main/).
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你可以从我们的[Hugging Face space](https://huggingface.co/lj1995/VoiceConversionWebUI/tree/main/)下载到这些模型。
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Here's a list of Pre-models and other files that RVC needs:
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以下是一份清单，包括了所有RVC所需的预模型和其他文件的名称:
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```bash
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./assets/hubert/hubert_base.pt
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@ -107,66 +95,39 @@ Here's a list of Pre-models and other files that RVC needs:
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./assets/uvr5_weights
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Additional downloads are required if you want to test the v2 version of the model.
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想测试v2版本模型的话，需要额外下载
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./assets/pretrained_v2
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If you want to test the v2 version model (the v2 version model has changed the input from the 256 dimensional feature of 9-layer Hubert+final_proj to the 768 dimensional feature of 12-layer Hubert, and has added 3 period discriminators), you will need to download additional features
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如果你正在使用Windows，则你可能需要这个文件，若ffmpeg和ffprobe已安装则跳过; ubuntu/debian 用户可以通过apt install ffmpeg来安装这2个库, Mac 用户则可以通过brew install ffmpeg来安装 (需要预先安装brew)
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./assets/pretrained_v2
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#If you are using Windows, you may also need these two files, skip if FFmpeg and FFprobe are installed
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ffmpeg.exe
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./ffmpeg
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https://huggingface.co/lj1995/VoiceConversionWebUI/blob/main/ffmpeg.exe
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ffprobe.exe
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./ffprobe
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https://huggingface.co/lj1995/VoiceConversionWebUI/blob/main/ffprobe.exe
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If you want to use the latest SOTA RMVPE vocal pitch extraction algorithm, you need to download the RMVPE weights and place them in the RVC root directory
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如果你想使用最新的RMVPE人声音高提取算法，则你需要下载音高提取模型参数并放置于RVC根目录
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https://huggingface.co/lj1995/VoiceConversionWebUI/blob/main/rmvpe.pt
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For AMD/Intel graphics cards users you need download:
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A卡I卡用户需要的dml环境要请下载
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https://huggingface.co/lj1995/VoiceConversionWebUI/blob/main/rmvpe.onnx
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```
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Intel ARC graphics cards users needs to run `source /opt/intel/oneapi/setvars.sh` command before starting Webui.
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Then use this command to start Webui:
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之后使用以下指令来启动WebUI:
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```bash
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python infer-web.py
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```
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If you are using Windows or macOS, you can download and extract `RVC-beta.7z` to use RVC directly by using `go-web.bat` on windows or `sh ./run.sh` on macOS to start Webui.
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如果你正在使用Windows 或 macOS，你可以直接下载并解压`RVC-beta.7z`，前者可以运行`go-web.bat`以启动WebUI，后者则运行命令`sh ./run.sh`以启动WebUI。
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## ROCm Support for AMD graphic cards (Linux only)
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To use ROCm on Linux install all required drivers as described [here](https://rocm.docs.amd.com/en/latest/deploy/linux/os-native/install.html).
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仓库内还有一份`小白简易教程.doc`以供参考。
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On Arch use pacman to install the driver:
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````
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pacman -S rocm-hip-sdk rocm-opencl-sdk
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````
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You might also need to set these environment variables (e.g. on a RX6700XT):
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````
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export ROCM_PATH=/opt/rocm
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export HSA_OVERRIDE_GFX_VERSION=10.3.0
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````
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Also make sure your user is part of the `render` and `video` group:
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````
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sudo usermod -aG render $USERNAME
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sudo usermod -aG video $USERNAME
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````
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After that you can run the WebUI:
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```bash
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python infer-web.py
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```
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## Credits
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## 参考项目
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+ [ContentVec](https://github.com/auspicious3000/contentvec/)
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+ [VITS](https://github.com/jaywalnut310/vits)
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+ [HIFIGAN](https://github.com/jik876/hifi-gan)
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+ [audio-slicer](https://github.com/openvpi/audio-slicer)
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+ [Vocal pitch extraction:RMVPE](https://github.com/Dream-High/RMVPE)
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+ The pretrained model is trained and tested by [yxlllc](https://github.com/yxlllc/RMVPE) and [RVC-Boss](https://github.com/RVC-Boss).
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## Thanks to all contributors for their efforts
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## 感谢所有贡献者作出的努力
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<a href="https://github.com/RVC-Project/Retrieval-based-Voice-Conversion-WebUI/graphs/contributors" target="_blank">
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<img src="https://contrib.rocks/image?repo=RVC-Project/Retrieval-based-Voice-Conversion-WebUI" />
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</a>
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